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- W4299528552 abstract "We develop a neural network model that relieves time-consuming trial-and-error computer experiments usually performed in problem-solving with networks where problems, including the traveling salesman problem, pattern matching and pattern classification/learning, are formulated as optimization problems with constraint. First, we specify and uniquely distinguish the model as a set of constituent functions that should comply with restrictive conditions. Next, we demonstrate that it is unified, i.e., it yields most current networks. Finally, we verify that it is constructive, i.e. we show a standard method that systematically constructs from a given optimization problem a particular network in that model to solve it." @default.
- W4299528552 created "2022-10-02" @default.
- W4299528552 date "2000-08-01" @default.
- W4299528552 modified "2023-09-30" @default.
- W4299528552 title "Papers to Appear in Forthcoming Issues" @default.
- W4299528552 doi "https://doi.org/10.1006/jagm.2000.1111" @default.
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